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license: apache-2.0 |
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# FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented Dialogue |
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We present our dialogue-pertaining model, FutureTOD, which distills future knowledge into the representation of the previous dialogue context using a self-training framework. Extensive experiments on diverse downstream dialogue tasks demonstrate the effectiveness of our model, especially its generalization, robustness, and ability to learn discriminative dialogue representations. |
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[This paper](https://arxiv.org/abs/2306.10315) has been accepted at the ACL 2023 Main Conference. |
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## Usage |
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We release our futuretod-base-v1.0 model here. You can use this model for downstream TOD tasks follow instructions in [FutureTOD](https://github.com/Zeng-WH/FutureTOD). |
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## Quotation |
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If you find our work helpful, please consider quoting the following papers. |
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``` |
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@article{zeng2023futuretod, |
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title={FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented Dialogue}, |
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author={Zeng, Weihao and He, Keqing and Wang, Yejie and Zeng, Chen and Wang, Jingang and Xian, Yunsen and Xu, Weiran}, |
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journal={arXiv preprint arXiv:2306.10315}, |
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year={2023} |
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} |
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``` |
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